## [1] TRUE
## [1] TRUE
## [1] FALSE
Match data to tree & fit PGLS in caper
## $tree_not_data
## [1] "Anodonthyla_boulengerii_Microhylidae"
## [2] "Leptobrachella_bidoupensis_Megophryidae"
## [3] "Microhyla_fissipes_Microhylidae"
## [4] "Microhyla_fusca_Microhylidae"
## [5] "Microhyla_marmorata_Microhylidae"
## [6] "Microhyla_pulverata_Microhylidae"
## [7] "Nasikabatrachus_sahyadrensis_Nasikabatrachidae"
##
## $data_not_tree
## character(0)
## [1] "Leptobrachella_bidoupensis_Megophryidae"
## [2] "Nasikabatrachus_sahyadrensis_Nasikabatrachidae"
## [3] "Anodonthyla_boulengerii_Microhylidae"
## [4] "Microhyla_pulverata_Microhylidae"
## [5] "Microhyla_fusca_Microhylidae"
## [6] "Microhyla_fissipes_Microhylidae"
## [7] "Microhyla_marmorata_Microhylidae"
## character(0)
##
## Call:
## pgls(formula = log10(cor_av) ~ log10(mass_av), data = frog.cdmass.comp,
## lambda = "ML", param.CI = 0.95)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.28753 -0.06242 -0.01143 0.04899 0.39358
##
## Branch length transformations:
##
## kappa [Fix] : 1.000
## lambda [ ML] : 0.875
## lower bound : 0.000, p = < 2.22e-16
## upper bound : 1.000, p = 3.1392e-08
## 95.0% CI : (0.775, 0.940)
## delta [Fix] : 1.000
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.368374 0.055494 6.6381 2.639e-10 ***
## log10(mass_av) 0.747702 0.031120 24.0266 < 2.2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.09844 on 211 degrees of freedom
## Multiple R-squared: 0.7323, Adjusted R-squared: 0.7311
## F-statistic: 577.3 on 1 and 211 DF, p-value: < 2.2e-16
Match data to tree & fit PGLS in caper
## $tree_not_data
## character(0)
##
## $data_not_tree
## [1] "Pleurodeles_waltl_gilled"
## character(0)
## [1] "Pleurodeles_waltl_gilled"
##
## Call:
## pgls(formula = log10(cor_av) ~ log10(rootmass_av), data = sal.cdmass.comp,
## lambda = "ML", param.CI = 0.95)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.031038 -0.005368 -0.000095 0.004781 0.041013
##
## Branch length transformations:
##
## kappa [Fix] : 1.000
## lambda [ ML] : 0.832
## lower bound : 0.000, p = 8.4377e-15
## upper bound : 1.000, p = 5.6595e-09
## 95.0% CI : (0.683, 0.922)
## delta [Fix] : 1.000
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.184679 0.057335 3.2211 0.001566 **
## log10(rootmass_av) 0.586098 0.051971 11.2773 < 2.2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.01006 on 150 degrees of freedom
## Multiple R-squared: 0.4588, Adjusted R-squared: 0.4552
## F-statistic: 127.2 on 1 and 150 DF, p-value: < 2.2e-16
Add traits to frog and salamander datasets
Stopping here because want to discuss before proceeding further.
Match data to tree & fit PGLS in caper
## $tree_not_data
## [1] "Leptobrachella_bidoupensis_Megophryidae"
## [2] "Microhyla_fissipes_Microhylidae"
## [3] "Microhyla_fusca_Microhylidae"
## [4] "Microhyla_marmorata_Microhylidae"
## [5] "Microhyla_pulverata_Microhylidae"
##
## $data_not_tree
## character(0)
## [1] "Leptobrachella_bidoupensis_Megophryidae"
## [2] "Microhyla_pulverata_Microhylidae"
## [3] "Microhyla_fusca_Microhylidae"
## [4] "Microhyla_fissipes_Microhylidae"
## [5] "Microhyla_marmorata_Microhylidae"
## character(0)
##
## Call:
## pgls(formula = log10(eye_av) ~ log10(mass_av), data = frog.edmass.comp,
## lambda = "ML", param.CI = 0.95)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.39281 -0.07739 -0.00560 0.06081 0.40551
##
## Branch length transformations:
##
## kappa [Fix] : 1.000
## lambda [ ML] : 0.961
## lower bound : 0.000, p = < 2.22e-16
## upper bound : 1.000, p = 0.012383
## 95.0% CI : (0.900, 0.994)
## delta [Fix] : 1.000
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.455710 0.062496 7.2918 5.916e-12 ***
## log10(mass_av) 0.822677 0.028023 29.3573 < 2.2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.1084 on 213 degrees of freedom
## Multiple R-squared: 0.8018, Adjusted R-squared: 0.8009
## F-statistic: 861.9 on 1 and 213 DF, p-value: < 2.2e-16
##
## Call:
## pgls(formula = log10(eye_av) ~ log10(rootmass_av), data = sal.cdmass.comp,
## lambda = "ML", param.CI = 0.95)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.0180704 -0.0036954 -0.0000669 0.0035026 0.0228160
##
## Branch length transformations:
##
## kappa [Fix] : 1.000
## lambda [ ML] : 0.845
## lower bound : 0.000, p = 3.0531e-11
## upper bound : 1.000, p = 2.8592e-06
## 95.0% CI : (0.658, 0.942)
## delta [Fix] : 1.000
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.398691 0.042603 9.3584 2.22e-16 ***
## log10(rootmass_av) 0.773017 0.041458 18.6458 < 2.2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.006815 on 136 degrees of freedom
## (14 observations deleted due to missingness)
## Multiple R-squared: 0.7188, Adjusted R-squared: 0.7167
## F-statistic: 347.7 on 1 and 136 DF, p-value: < 2.2e-16
Match data to tree & fit PGLS in caper
## [1] "OK"
## character(0)
## character(0)
##
## Call:
## pgls(formula = log10(TD_av) ~ log10(mass_av), data = fishes.comp,
## lambda = "ML", param.CI = 0.95)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.051652 -0.008660 -0.000058 0.008999 0.061939
##
## Branch length transformations:
##
## kappa [Fix] : 1.000
## lambda [ ML] : 0.984
## lower bound : 0.000, p = < 2.22e-16
## upper bound : 1.000, p = 0.00017103
## 95.0% CI : (0.964, 0.996)
## delta [Fix] : 1.000
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.423092 0.195990 2.1587 0.03148 *
## log10(mass_av) 0.742976 0.031432 23.6379 < 2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.01431 on 388 degrees of freedom
## (46 observations deleted due to missingness)
## Multiple R-squared: 0.5902, Adjusted R-squared: 0.5891
## F-statistic: 558.7 on 1 and 388 DF, p-value: < 2.2e-16
Note that the salamander eye size dataset is msising the species with the smallest eyes (those had cornea measurements only), so that pushes the regression line up quite a bit.
Match data to tree & fit PGLS in caper
## [1] "OK"
## character(0)
## character(0)
##
## Call:
## pgls(formula = log10(eye_av) ~ log10(svl_av), data = frog.edsvl.comp,
## lambda = "ML", param.CI = 0.95)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.34569 -0.05473 0.00599 0.06458 0.31770
##
## Branch length transformations:
##
## kappa [Fix] : 1.000
## lambda [ ML] : 0.963
## lower bound : 0.000, p = < 2.22e-16
## upper bound : 1.000, p = 0.022769
## 95.0% CI : (0.902, 0.996)
## delta [Fix] : 1.000
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -0.664341 0.068331 -9.7224 < 2.2e-16 ***
## log10(svl_av) 0.837692 0.024418 34.3065 < 2.2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.09626 on 218 degrees of freedom
## Multiple R-squared: 0.8437, Adjusted R-squared: 0.843
## F-statistic: 1177 on 1 and 218 DF, p-value: < 2.2e-16
##
## Call:
## pgls(formula = log10(eye_av) ~ log10(svl_av), data = sal.cdmass.comp,
## lambda = "ML", param.CI = 0.95)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.0173372 -0.0021347 0.0006661 0.0041418 0.0154655
##
## Branch length transformations:
##
## kappa [Fix] : 1.000
## lambda [ ML] : 0.749
## lower bound : 0.000, p = 3.9968e-14
## upper bound : 1.000, p = 1.1559e-08
## 95.0% CI : (0.506, 0.898)
## delta [Fix] : 1.000
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -0.839890 0.079508 -10.564 < 2.2e-16 ***
## log10(svl_av) 0.782916 0.039652 19.745 < 2.2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.005834 on 136 degrees of freedom
## (14 observations deleted due to missingness)
## Multiple R-squared: 0.7414, Adjusted R-squared: 0.7395
## F-statistic: 389.9 on 1 and 136 DF, p-value: < 2.2e-16
## $tree_not_data
## [1] "Acanthodactylus_boskianus" "Acanthodactylus_cantoris"
## [3] "Acanthodactylus_longipes" "Acanthodactylus_pardalis"
## [5] "Aeluroscalabotes_felinus" "Agkistrodon_piscivorus"
## [7] "Amblyrhynchus_cristatus" "Ameiva_ameiva"
## [9] "Anolis_trinitatis" "Basiliscus_basiliscus"
## [11] "Basiliscus_vittatus" "Bellatorias_frerei"
## [13] "Boa_constrictor" "Broadleysaurus_major"
## [15] "Brookesia_superciliaris" "Callisaurus_draconoides"
## [17] "Calotes_mystaceus" "Calotes_versicolor"
## [19] "Chalcides_ocellatus" "Chamaeleo_africanus"
## [21] "Chamaeleo_chamaeleon" "Chamaesaura_macrolepis"
## [23] "Coleonyx_elegans" "Coleonyx_variegatus"
## [25] "Cordylus_cordylus" "Cordylus_niger"
## [27] "Crotaphytus_bicinctores" "Crotaphytus_collaris"
## [29] "Ctenosaura_hemilopha" "Ctenosaura_similis"
## [31] "Cyrtodactylus_louisiadensis" "Dipsosaurus_dorsalis"
## [33] "Dracaena_guianensis" "Draco_melanopogon"
## [35] "Eremias_persica" "Eublepharis_hardwickii"
## [37] "Eublepharis_macularius" "Eugongylus_rufescens"
## [39] "Eumeces_schneideri" "Furcifer_lateralis"
## [41] "Furcifer_verrucosus" "Gallotia_atlantica"
## [43] "Gallotia_galloti" "Gekko_swinhonis"
## [45] "Gerrhosaurus_nigrolineatus" "Glaphyromorphus_nigricaudis"
## [47] "Gonatodes_ocellatus" "Gonocephalus_grandis"
## [49] "Heliobolus_lugubris" "Heloderma_suspectum"
## [51] "Hemidactylus_platycephalus" "Iguana_iguana"
## [53] "Karusasaurus_polyzonus" "Lacerta_agilis"
## [55] "Lacerta_viridis" "Leiocephalus_carinatus"
## [57] "Leiolepis_belliana" "Lepidodactylus_lugubris"
## [59] "Lepidophyma_gaigeae" "Liopholis_whitii"
## [61] "Lophognathus_longirostris" "Lygodactylus_picturatus"
## [63] "Meroles_anchietae" "Meroles_knoxii"
## [65] "Meroles_squamulosa" "Mesalina_guttulata"
## [67] "Narudasia_festiva" "Natrix_natrix"
## [69] "Phelsuma_astriata" "Phelsuma_madagascariensis"
## [71] "Phrynosoma_blainvillii" "Phrynosoma_cornutum"
## [73] "Phyllodactylus_reissii" "Platysaurus_guttatus"
## [75] "Platysaurus_intermedius" "Plestiodon_skiltonianus"
## [77] "Podarcis_muralis" "Pristurus_carteri"
## [79] "Pseudopus_apodus" "Python_molurus"
## [81] "Quedenfeldtia_moerens" "Saara_hardwickii"
## [83] "Sauromalus_ater" "Sceloporus_grammicus"
## [85] "Sceloporus_horridus" "Sceloporus_jarrovii"
## [87] "Sceloporus_magister" "Sceloporus_occidentalis"
## [89] "Scincus_mitranus" "Scincus_scincus"
## [91] "Sphaerodactylus_copei" "Sphenodon_punctatus"
## [93] "Takydromus_septentrionalis" "Tarentola_mauritanica"
## [95] "Thamnophis_melanogaster" "Thamnophis_sirtalis"
## [97] "Tiliqua_gigas" "Timon_lepidus"
## [99] "Trachylepis_perrotetii" "Trioceros_bitaeniatus"
## [101] "Trioceros_hoehnelii" "Tropidurus_hispidus"
## [103] "Tupinambis_teguixin" "Uma_exsul"
## [105] "Uranoscodon_superciliosus" "Uromastyx_aegyptia"
## [107] "Varanus_indicus" "Varanus_salvator"
## [109] "Xantusia_henshawi" "Xantusia_riversiana"
## [111] "Xantusia_vigilis"
##
## $data_not_tree
## character(0)
## [1] "Sphenodon_punctatus" "Eremias_persica"
## [3] "Mesalina_guttulata" "Acanthodactylus_pardalis"
## [5] "Acanthodactylus_longipes" "Acanthodactylus_boskianus"
## [7] "Acanthodactylus_cantoris" "Heliobolus_lugubris"
## [9] "Meroles_anchietae" "Meroles_squamulosa"
## [11] "Meroles_knoxii" "Podarcis_muralis"
## [13] "Takydromus_septentrionalis" "Timon_lepidus"
## [15] "Lacerta_agilis" "Lacerta_viridis"
## [17] "Gallotia_galloti" "Gallotia_atlantica"
## [19] "Ameiva_ameiva" "Tupinambis_teguixin"
## [21] "Dracaena_guianensis" "Brookesia_superciliaris"
## [23] "Trioceros_bitaeniatus" "Trioceros_hoehnelii"
## [25] "Chamaeleo_chamaeleon" "Chamaeleo_africanus"
## [27] "Furcifer_lateralis" "Furcifer_verrucosus"
## [29] "Leiolepis_belliana" "Lophognathus_longirostris"
## [31] "Draco_melanopogon" "Gonocephalus_grandis"
## [33] "Calotes_versicolor" "Calotes_mystaceus"
## [35] "Uromastyx_aegyptia" "Saara_hardwickii"
## [37] "Phrynosoma_blainvillii" "Phrynosoma_cornutum"
## [39] "Uma_exsul" "Callisaurus_draconoides"
## [41] "Sceloporus_magister" "Sceloporus_occidentalis"
## [43] "Sceloporus_horridus" "Sceloporus_jarrovii"
## [45] "Sceloporus_grammicus" "Anolis_trinitatis"
## [47] "Leiocephalus_carinatus" "Basiliscus_vittatus"
## [49] "Basiliscus_basiliscus" "Dipsosaurus_dorsalis"
## [51] "Sauromalus_ater" "Iguana_iguana"
## [53] "Amblyrhynchus_cristatus" "Ctenosaura_hemilopha"
## [55] "Ctenosaura_similis" "Uranoscodon_superciliosus"
## [57] "Tropidurus_hispidus" "Crotaphytus_bicinctores"
## [59] "Crotaphytus_collaris" "Pseudopus_apodus"
## [61] "Heloderma_suspectum" "Varanus_salvator"
## [63] "Varanus_indicus" "Boa_constrictor"
## [65] "Python_molurus" "Agkistrodon_piscivorus"
## [67] "Natrix_natrix" "Thamnophis_melanogaster"
## [69] "Thamnophis_sirtalis" "Platysaurus_guttatus"
## [71] "Platysaurus_intermedius" "Karusasaurus_polyzonus"
## [73] "Chamaesaura_macrolepis" "Cordylus_niger"
## [75] "Cordylus_cordylus" "Broadleysaurus_major"
## [77] "Gerrhosaurus_nigrolineatus" "Lepidophyma_gaigeae"
## [79] "Xantusia_riversiana" "Xantusia_vigilis"
## [81] "Xantusia_henshawi" "Glaphyromorphus_nigricaudis"
## [83] "Eugongylus_rufescens" "Trachylepis_perrotetii"
## [85] "Liopholis_whitii" "Bellatorias_frerei"
## [87] "Tiliqua_gigas" "Chalcides_ocellatus"
## [89] "Plestiodon_skiltonianus" "Eumeces_schneideri"
## [91] "Scincus_scincus" "Scincus_mitranus"
## [93] "Aeluroscalabotes_felinus" "Eublepharis_macularius"
## [95] "Eublepharis_hardwickii" "Coleonyx_elegans"
## [97] "Coleonyx_variegatus" "Pristurus_carteri"
## [99] "Quedenfeldtia_moerens" "Sphaerodactylus_copei"
## [101] "Gonatodes_ocellatus" "Narudasia_festiva"
## [103] "Lygodactylus_picturatus" "Phelsuma_astriata"
## [105] "Phelsuma_madagascariensis" "Lepidodactylus_lugubris"
## [107] "Gekko_swinhonis" "Cyrtodactylus_louisiadensis"
## [109] "Hemidactylus_platycephalus" "Tarentola_mauritanica"
## [111] "Phyllodactylus_reissii"
## character(0)
##
## Call:
## pgls(formula = log10(TD_av) ~ log10(svl_av) * Subgroup, data = squam.edsvl.comp,
## lambda = "ML", param.CI = 0.95)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.053486 -0.009735 -0.002637 0.008329 0.055101
##
## Branch length transformations:
##
## kappa [Fix] : 1.000
## lambda [ ML] : 1.000
## lower bound : 0.000, p = 0.00023366
## upper bound : 1.000, p = 1
## 95.0% CI : (0.794, NA)
## delta [Fix] : 1.000
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -1.883245 0.244792 -7.6933 3.988e-12 ***
## log10(svl_av) 0.858776 0.063681 13.4855 < 2.2e-16 ***
## Subgroupgeckos 0.735057 0.351075 2.0937 0.03834 *
## log10(svl_av):Subgroupgeckos 0.081401 0.125112 0.6506 0.51650
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.01669 on 123 degrees of freedom
## Multiple R-squared: 0.6778, Adjusted R-squared: 0.6699
## F-statistic: 86.23 on 3 and 123 DF, p-value: < 2.2e-16
Note that the salamander eye size dataset is missing the species with the smallest eyes (those had cornea measurements only), so that pushes the regression line up quite a bit.
We can put these plots together to make a paneled figure
## quartz_off_screen
## 2